An Introduction to Genetic Algorithms
โ Scribed by Melanie Mitchell
- Publisher
- The MIT Press
- Year
- 1996
- Tongue
- English
- Leaves
- 224
- Series
- Complex Adaptive Systems
- Edition
- First printing.
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Mitchell's book provvides an in-depth intodution to genetic algorithms in areas such as machine learning , scientific modeling, and "artificial life". An Introduction to Genetic Algorithms is a terse and accesible text allowing readers to implement and experiment with genetic algorithms (GA's) - specifically GA's in machine learning, scientific modeling, and "artificial life". Included are thought experiments and exercises to enforce ideas presented in each chapter of the text. Chapter one introduces GA terms and history while describing two applications in detail. Chapter two and three explore the use of GA's in problem solving and scientific modeling. The fourth chapter gives a thorough overview of the theoretical foundations of GA's, while the fifth tackles implementation of GA's. The last chapter surveys some currently unanswered questions and considers the future of GA's. Inlcuded in two appendices are substantial references to other resources on genetic algorithms"
๐ SIMILAR VOLUMES
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to
I have to agree with all of johnnied7 criticisms. This book is pitched at a level too advanced for an introduction. It also reads and is structured like a research paper. Not recommended.
Book, 64 p, March 2002<br/>Contents<br/>Optimization and hill climbing<br/>The simplex method<br/>Iterated simplex<br/>A set of test problems<br/>Performance of the simplex and iterated simplex methods<br/>Evolution optimization and genetic algorithms<br/>Biological evolution<br/>The power of cumula